Reliable serum markers for cancer diagnosis should lead to reduced mortality and morbidity through earlier initial detection of cancer and recurring tumors. Unfortunately, most of the handful of known serum diagnostic targets do not show adequate specificity. However, these serum markers have usually been identified one-at-a-time and based on indirect clues rather than through systematic analyses of serum proteins. A systematic proteomics search for tumor-specific serum proteins is much more likely to identify better serum markers and/or identify groups of proteins secreted by the tumors that will be more reliable than any one or two individual serological markers. Effective serum proteomics-based analyses will require development of new methods capable of detecting proteins at the low ng/ml level or less, because cancer biomarkers are typically low abundance proteins in the presence of very abundant serum proteins, The central working hypothesis of this proposal is that systematic analysis of biological fluids with new proteome methods will produce either several novel serological markers or alternatively will define biosignatures that can be used to diagnose diseases including cancer. The two major goals of this proposal are:1) to develop multi-stage serum prefractionation strategies coupled with improved high sensitivity 1-D gel and nanocapillary LC-MS/MS methods for systematic identifications of tumor-specific proteins, and 2) to use these new methods to identify biomarkers secreted by human ovarian tumors into SCID mouse serum. The feasibility of using serum from SCID mice containing human tumors to identify secreted tumor proteins has recently been demonstrated in this laboratory. Ovarian cancer will be studied because early tumors are asymptomatic, the organ is relatively inaccessible to examination, and there are no reliable early detection methods. As a result, ovarian cancer has a very poor survival rate and is the leading cause of death from gynecological malignancies and the fourth most common cause of cancer deaths in women. The four Specific Aims are: 1) Develop a robust nanoscale in-gel digestion method for higher sensitivity protein identification; 2) Develop and test an automated high throughput nanoscale in-gel digestion method; 3) Compare the 1-D gel pixelation approach with MudPIT analyses using prefractionated serum; and 4) Produce and systematically evaluate serum samples from SCID mice with ovarian tumors